open science

PD-31 - PySAL and Spatial Statistics Libraries

As spatial statistics are essential to the geographical inquiry, accessible and flexible software offering relevant functionalities is highly desired. Python Spatial Analysis Library (PySAL) represents an endeavor towards this end. It is an open-source python library and ecosystem hosting a wide array of spatial statistical and visualization methods. Since its first public release in 2010, PySAL has been applied to address various research questions, used as teaching materials for pedagogical purposes in regular classes and conference workshops serving a wide audience, and integrated into general GIS software such as ArcGIS and QGIS. This entry first gives an overview of the history and new development with PySAL. This is followed by a discussion of PySAL’s new hierarchical structure, and two different modes of accessing PySAL’s functionalities to perform various spatial statistical tasks, including exploratory spatial data analysis, spatial regression, and geovisualization. Next, a discussion is provided on how to find and utilize useful materials for studying and using spatial statistical functions from PySAL and how to get involved with the PySAL community as a user and prospective developer. The entry ends with a brief discussion of future development with PySAL.

CP-26 - eScience, the Evolution of Science

Science—and research more broadly—face many challenges as its practitioners struggle to accommodate new challenges around reproducibility and openness.  The current practice of science limits access to knowledge, information and infrastructure, which in turn leads to inefficiencies, frustrations and a lack of rigor.  Many useful research outcomes are never used because they are too difficult to find, or to access, or to understand.

New computational methods and infrastructure provide opportunities to reconceptualize how science is conducted, how it is shared, how it is evaluated and how it is reused.  And new data sources changed what can be known, and how well, and how frequently.  This article describes some of the major themes of eScience/eResearch aimed at improving the process of doing science.

PD-31 - PySAL and Spatial Statistics Libraries

As spatial statistics are essential to the geographical inquiry, accessible and flexible software offering relevant functionalities is highly desired. Python Spatial Analysis Library (PySAL) represents an endeavor towards this end. It is an open-source python library and ecosystem hosting a wide array of spatial statistical and visualization methods. Since its first public release in 2010, PySAL has been applied to address various research questions, used as teaching materials for pedagogical purposes in regular classes and conference workshops serving a wide audience, and integrated into general GIS software such as ArcGIS and QGIS. This entry first gives an overview of the history and new development with PySAL. This is followed by a discussion of PySAL’s new hierarchical structure, and two different modes of accessing PySAL’s functionalities to perform various spatial statistical tasks, including exploratory spatial data analysis, spatial regression, and geovisualization. Next, a discussion is provided on how to find and utilize useful materials for studying and using spatial statistical functions from PySAL and how to get involved with the PySAL community as a user and prospective developer. The entry ends with a brief discussion of future development with PySAL.

CP-26 - eScience, the Evolution of Science

Science—and research more broadly—face many challenges as its practitioners struggle to accommodate new challenges around reproducibility and openness.  The current practice of science limits access to knowledge, information and infrastructure, which in turn leads to inefficiencies, frustrations and a lack of rigor.  Many useful research outcomes are never used because they are too difficult to find, or to access, or to understand.

New computational methods and infrastructure provide opportunities to reconceptualize how science is conducted, how it is shared, how it is evaluated and how it is reused.  And new data sources changed what can be known, and how well, and how frequently.  This article describes some of the major themes of eScience/eResearch aimed at improving the process of doing science.

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